The goal of this study is to ensure that pregnant patients have the resources and support needed to access Prenatal Screening \& Diagnostic Testing (PS\&D) in an informed and evidence-based fashion by developing an innovative digital tool to support patients' decision-making and contributing fundamental knowledge to advance science in a way that promotes patients' access to new prenatal applications of genomic science and technology. Our central hypothesis is that, by focusing on patient engagement as a key driver to improve patient outcomes, the use of an evidence-based artificial-intelligence (AI) powered patient engagement tool will increase patients' ability to seek information and structure a decision-making process that, in turn, increases informed decisions about PS\&D and decreases decisional conflict associated with those decisions. Using data from NEST (Ensuring Patients Informed Access to NIPT \[non-invasive prenatal testing\]), the investigators designed the next iteration of NEST, a point-of care shared decision-making tool powered by artificial intelligence (AI) to provide a personalized and dynamic decision support tool: Obstetric Prenatal Genetic Testing Engagement Solution (OPUS). OPUS is an AI-enabled healthcare chatbot (a computer program capable of processing and simulating human conversation) that provides patients with personalized information and decision-making support at different stages of the PS\&D pathway. It functions using a series of questions contained in the NEST with a branching logic sequence of questions and answers based on the responses to and from the patient, using a conversational and adaptable interaction. It also contains nested tiers of information, ranging from introductory to detailed information about patient engagement, health literacy, the different PS\&D options, and resources to learn about insurance coverage for PS\&D. OPUS was designed to be accessed by patients with different technological resources and preferences, using a cell phone, a mobile device, or a computer.
Prenatal Disorder
The goal of this study is to ensure that pregnant patients have the resources and support needed to access Prenatal Screening \& Diagnostic Testing (PS\&D) in an informed and evidence-based fashion by developing an innovative digital tool to support patients' decision-making and contributing fundamental knowledge to advance science in a way that promotes patients' access to new prenatal applications of genomic science and technology. Our central hypothesis is that, by focusing on patient engagement as a key driver to improve patient outcomes, the use of an evidence-based artificial-intelligence (AI) powered patient engagement tool will increase patients' ability to seek information and structure a decision-making process that, in turn, increases informed decisions about PS\&D and decreases decisional conflict associated with those decisions. Using data from NEST (Ensuring Patients Informed Access to NIPT \[non-invasive prenatal testing\]), the investigators designed the next iteration of NEST, a point-of care shared decision-making tool powered by artificial intelligence (AI) to provide a personalized and dynamic decision support tool: Obstetric Prenatal Genetic Testing Engagement Solution (OPUS). OPUS is an AI-enabled healthcare chatbot (a computer program capable of processing and simulating human conversation) that provides patients with personalized information and decision-making support at different stages of the PS\&D pathway. It functions using a series of questions contained in the NEST with a branching logic sequence of questions and answers based on the responses to and from the patient, using a conversational and adaptable interaction. It also contains nested tiers of information, ranging from introductory to detailed information about patient engagement, health literacy, the different PS\&D options, and resources to learn about insurance coverage for PS\&D. OPUS was designed to be accessed by patients with different technological resources and preferences, using a cell phone, a mobile device, or a computer.
Engaging Patients in Prenatal Genetic Testing Decisions as a Pathway to Improve Obstetric Outcomes
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Neighborhood Family Practice, Cleveland, Ohio, United States, 44102
MetroHealth Medical Center, Cleveland, Ohio, United States, 44109
Cleveland Clinic, Cleveland, Ohio, United States, 44195
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
For general information about clinical research, read Learn About Studies.
18 Years to 50 Years
FEMALE
No
The Cleveland Clinic,
Ruth Farrell, MD, MA, PRINCIPAL_INVESTIGATOR, The Cleveland Clinic
2027-02-28